Numerous implantable medical devices (IMDs) are configured for monitoring and storing physiological data for use in diagnosing a patient condition or managing medical therapies. Such devices include implantable cardiac pacemakers, implantable cardioverter defibrillators (ICDs), hemodynamic monitors, subcutaneous ECG monitors, neural stimulators, and the like. Detection of a physiological event, such as an arrhythmia, generally triggers storage of summary information relating to the event in an episode log and detailed physiological signal data is stored in an episode record, e.g. the ECG signal over an interval of time including the event detection and corresponding marker channel data. Such physiological signal storage is useful to a clinician in diagnosing patient condition and managing patient therapies. An IMD may be capable of detecting numerous types of physiological events based on sensed signals but generally has limited memory capacity for storing data relating to detected physiological events due to physical size constraints.
Storage of a physiological signal in an episode record requires considerably more memory than storage of summary data in an episode log. In order to ensure that the episodes stored in an episode log and episodes stored in an episode record correspond to each other and are available for interrogation, IMD memory is typically allocated separately for episode logs and episode records for each of a number of a different types of physiological events. However, a patient may experience multiple episodes of one event type and few or no episodes of other event types. As a result, memory allocated for storing episode records for one type of event may be under-allocated. The allocated memory may be quickly filled with new episodes overwriting old episodes of the same event type. Meanwhile, memory allocated for other rarely-occurring event types is underutilized. As implantable devices become smaller to avoid patient discomfort and ease implant procedures, memory capacity becomes more limited, increasing the importance of efficient management of physiological data storage.